Deep Learning-Based Reconstruction Algorithm With Lung Enhancement Filter for Chest CT: Effect on Image Quality and Ground Glass Nodule Sharpness.

OBJECTIVE: To assess the effect of a new lung enhancement filter combined with deep learning image reconstruction (DLIR) algorithm on image quality and ground-glass nodule (GGN) sharpness compared to hybrid iterative reconstruction or DLIR alone. MATERIALS AND METHODS: Five artificial spherical GGNs with various densities (-250, -350, -450, -550, and -630 Hounsfield units) and 10 mm in diameter were placed in a thorax anthropomorphic phantom. Four scans at four different radiation dose levels were performed using a 256-slice CT (Revolution Apex CT, GE Healthcare). Each scan was reconstructed using three different reconstruction algorithms: adaptive statistical iterative reconstruction-V at a level of 50% (AR50), Truefidelity (TF), which is a DLIR method, and TF with a lung enhancement filter (TF + Lu). Thus, 12 sets of reconstructed images were obtained and analyzed. Image noise, signal-to-noise ratio, and contrast-to-noise ratio were compared among the three reconstruction algorithms. Nodule sharpness was compared among the three reconstruction algorithms using the full-width at half-maximum value. Furthermore, subjective image quality analysis was performed. RESULTS: AR50 demonstrated the highest level of noise, which was decreased by using TF + Lu and TF alone (P = 0.001). TF + Lu significantly improved nodule sharpness at all radiation doses compared to TF alone (P = 0.001). The nodule sharpness of TF + Lu was similar to that of AR50. Using TF alone resulted in the lowest nodule sharpness. CONCLUSION: Adding a lung enhancement filter to DLIR (TF + Lu) significantly improved the nodule sharpness compared to DLIR alone (TF). TF + Lu can be an effective reconstruction technique to enhance image quality and GGN evaluation in ultralow-dose chest CT scans.

Improving the radiographic image analysis of the classic metaphyseal lesion via conditional diffusion models.

The classic metaphyseal lesion (CML) is a unique fracture highly specific for infant abuse. This fracture is often subtle in radiographic appearance and commonly occurs in the distal tibia. The development of an automated model that can accurately identify distal tibial radiographs with CMLs is important to assist radiologists in detecting these fractures. However, building such a model typically requires a large and diverse training dataset. To address this problem, we propose a novel diffusion model for data augmentation called masked conditional diffusion model (MaC-DM). In contrast to previous generative models, our approach produces a wide range of realistic-appearing synthetic images of distal tibial radiographs along with their associated segmentation masks. MaC-DM achieves this by incorporating weighted segmentation masks of the distal tibias and CML fracture sites as image conditions for guidance. The augmented images produced by MaC-DM significantly enhance the performance of various commonly used classification models, accurately distinguishing normal distal tibial radiographs from those with CMLs. Additionally, it substantially improves the performance of different segmentation models, accurately labeling areas of the CMLs on distal tibial radiographs. Furthermore, MaC-DM can control the size of the CML fracture in the augmented images.

Scale-based landmark for internal organs assessments of common carp (Cyprinus carpio) during digital radiography and ultrasonography imaging.

Medical imaging techniques such as digital radiography and ultrasonography are non-invasive and provide precise results for examining internal organs and structures within fish. Their effectiveness can be further enhanced by using body parts like scales as markers for the organs beneath them. This study utilized the number of scales as landmarks in digital radiography and ultrasonography to non-invasively evaluate the muscles, bones, and images of internal and reproductive organs of common carp (Cyprinus carpio). Digital radiography was performed in the dorsoventral and lateral views of the fish, whereas ultrasonography was conducted in longitudinal and transverse views on sequence scale numbers with brightness and colour Doppler-modes. Digital radiography of the common carp revealed the whole-body morphology, including the bony parts from the head, pectoral fins, dorsal fins, pelvic fins, anal fins, and vertebrae to the tail that appeared radiopaque. Internal organs were also observed, with the swim bladder and heart appeared radiolucent, while the intestines, liver, testes, and ovaries appeared radiopaque. Ultrasonography in brightness mode displayed the digestive organs, reproductive organs, and muscle thickness. Additionally, colour Doppler mode demonstrated blood flow within the heart's ventricle.

Impact of reducing iodinated intravenous contrast volume in brain CT on image diagnostic quality.

PURPOSE: To investigate whether reducing the volume of intravenous iodinated contrast material injected during brain computed tomography (CT) provides reliable and accurate imaging without compromising diagnostic accuracy. METHODS: This prospective study enrolled patients undergoing enhanced brain CT at a single tertiary hospital. Subjects who agreed to participate received a reduced dose of 60 ml contrast. The images were compared to an age and gender-matched control group who received the conventional 80 cc dose. Neuroradiologists assessed image quality and interpretation using a 5-point Likert scale with six specific domains. Based on ICC, inter-rater reliability was high at 0.873. Multiple linear regression predicted overall diagnostic accuracy based on contrast dose, age, and gender. Visual Grading Characteristics (VGC) analysis was also performed to quantify regional brain enhancement differences between the two contrast groups. RESULTS: The study included 47 patients in the 60 cc group and 55 in the 80 cc control group. The results showed the 80 cc group had significantly higher enhancement ratings compared to 60 cc for all six structures assessed. The differences between groups ranged from -0.241 to -0.433 (p < 0.001) on the 5-point scale.The VGC analysis confirmed significantly greater brain parenchymal enhancement in the 80 cc group compared to the 60 cc group. CONCLUSION: The findings indicate that reducing the intravenous iodinated contrast material volume during brain CT from 80 cc to 60 cc leads to a statistically significant reduction in image quality and diagnostic accuracy. Further research with larger cohorts is needed to confirm these findings and assess the clinical impact of these differences.

Contrast enhancement boost improves the image quality of CT angiography derived from 80-kVp cerebral CT perfusion data.

RATIONALE AND OBJECTIVE: To investigate the impact of the contrast enhancement boost (CE-boost) technique on the image quality of CT angiography (CTA) derived from 80-kVp cerebral CT perfusion (CTP) data, and to compare it with conventional CTApeak as well as other currently employed methods for enhancing CTA images, such as CTAtMIP and CTAtAve extracted from CTP. MATERIALS AND METHODS: The data of forty-seven patients who underwent CTP at 80 kVp were retrospectively collected. Four sets of images: CTApeak, CTAtMIP, CTAtAve, and CE-boost images. The CTApeak image represents the arterial phase at its peak value, captured as a single time point. CTAtMIP and CTAtAve are 4D CTA images that provide maximum density projection and average images from the three most prominent time points. CE-boost is a postprocessing technique used to enhance contrast in the arterial phase at its peak value. We compared the average CT value, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the internal carotid artery (ICA) and basilar artery (BA) among the four groups. Image quality was evaluated using a 5-point scale. RESULTS: The CE-boost demonstrated and CNR in the ICA and BA (all p < 0.001). Compared with the other three CTA reconstructed images, the CE-boost images had the best subjective image quality, with the highest scores of 4.77 ± 0.43 and 4.87 ± 0.34 for each reader (all p < 0.001). CONCLUSION: Compared with other currently used techniques,CE-boost enhances the image quality of CTA derived from 80-kVp CTP data, leading to improved visualization of intracranial arteries.

Evaluation of the performance of digital x-ray systems in pelvis radiography.

The aim of this study was to investigate the performance of eight digital radiography systems and to optimise the dose-image quality relationship for digital pelvis radiography. The study involved eight digital radiography systems used for general examinations at Vilnius University Hospital Santaros Klinikos. An anthropomorphic pelvic phantom (CIRS, US) was used to simulate a patient undergoing clinical pelvis radiography. Dose quantities entrance surface dose, dose area product (DAP) and exposure parameters (kVp, mA, mAs) were measured and the effects on the images were evaluated, considering physical contrast to noise ratio (CNR) and observer-based evaluations as image quality metrics. Increasing the tube voltage by 5 kVp from standard protocol led to a reduction in radiation dose (DAP) by 12%-20% with a slight impact on image quality (CNR decreases by 2%-10%). There was an inter-observer variability in image rating across different equipment (kappa value between 0 and 0.3); however, both observers agreed that increasing kVp up to 85-90 kV had no effect on perceived image quality. The results indicate that optimisation strategies should be tailored specifically for each x-ray system since significant performance differences and wide variations in radiation dose exist across various digital radiography systems used in clinical settings. The use of high kVp can be used for dose optimisation in digital pelvis radiography without compromising image diagnostic accuracy.

A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) algorithms on the conventional enhanced and CE-boost (contrast-enhancement-boost) images of indirect computed tomography venography (CTV) of lower extremities. MATERIALS AND METHODS: In this retrospective study, seventy patients who underwent CTV from June 2021 to October 2022 to assess deep vein thrombosis and varicose veins were included. Unenhanced and enhanced images were reconstructed for AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images were obtained using subtraction software. Objective and subjective image qualities were assessed, and radiation doses were recorded. RESULTS: The CT values of the inferior vena cava (IVC), femoral vein ( FV), and popliteal vein (PV) in the CE-boost images were approximately 1.3 (1.31-1.36) times higher than in those of the enhanced images. There were no significant differences in mean CT values of IVC, FV, and PV between AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images. Noise in AiCE, AiCE-boost images was significantly lower than in AIDR 3D and AIDR 3D-boost images ( P < 0.05). The SNR (signal-to-noise ratio), CNR (contrast-to-noise ratio), and subjective scores of AiCE-boost images were the highest among 4 groups, surpassing AiCE, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: In indirect CTV of the lower extremities images, DLR with the CE-boost technique could decrease the image noise and improve the CT values, SNR, CNR, and subjective image scores. AiCE-boost images received the highest subjective image quality score and were more readily accepted by radiologists.

Patient dose and associated exposure parameters in pelvic x-ray examinations: dependence on radiographic system.

Technological differences between computed radiography (CR) and digital radiography (DR) systems can influence patient doses and exposure parameters in pelvic x-ray examinations. The presence of radiosensitive organs in the pelvic region underscores the need to optimize these parameters for both CR and DR systems. This prospective study aimed to compare the patient doses and exposure parameters for adult patients undergoing pelvic x-ray examinations using CR and DR systems, based on data from Sri Lanka. The study included data from 56 x-ray examinations, with 25 using CR and 31 using DR. Patient demographic characteristics and exposure parameters (kVp: kilovoltage peak, mAs: tube current-exposure time product) were recorded, and patient doses were measured in terms of the kerma-area product (PKA) using a PKA meter. Despite similar mean weight and body mass index (BMI), the CR systems showed significantly higher mean kVp (7.4%), mAs (16.4%), and PKA (29.7%) than the DR systems (CR - kVp: 73.2, mAs: 37.8, PKA: 2.29 Gy cm2; DR - kVp: 67.8, mAs: 31.6, PKA: 1.61 Gy cm2). The Mann-Whitney U test revealed statistically significant differences in PKA and kVp between the CR and DR systems (p < 0.05). Furthermore, even with lower patient weight and BMI, the mean mAs and PKA in this study were substantially higher than those reported in the literature for both CR and DR systems. These results suggest the need to optimize current mAs settings for the studied hospitals and introduce radiographic system-specific exposure parameters and reference dose levels for pelvic x-ray examinations in order to enhance patient protection.

Evaluating the impact of delayed-phase imaging in Contrast-Enhanced Mammography on breast cancer staging: A comparative study of abbreviated versus complete protocol.

PURPOSE: Contrast-enhanced mammography (CEM) is an innovative imaging tool for breast cancer detection, involving intravenous injection of a contrast medium and the assessment of lesion enhancement in two phases: early and delayed. The aim of the study was to analyze the topographic concordance of lesions detected in the early- versus delayed phase acquisitions. MATERIALS AND METHODS: Approved by the Ethics Committee (No. 118/20), this prospective study included 100 women with histopathological confirmed breast neoplasia (B6) at the Radiodiagnostics Department of the Maggiore della Carità Hospital of Novara, Italy from May 1, 2021, to October 17, 2022. Participants underwent CEM examinations using a complete protocol, encompassing both early- and delayed image acquisitions. Three experienced radiologists blindly analyzed the CEM images for contrast enhancement to determine the topographic concordance of the identified lesions. Two readers assessed the complete study (protocol A), while one reader assessed the protocol without the delayed phase (protocol B). The average glandular dose (AGD) of the entire procedure was also evaluated. RESULTS: The analysis demonstrated high concordance among the three readers in the topographical identification of lesions within individual quadrants of both breasts, with a Cohen's κ > 0.75, except for the lower inner quadrant of the right breast and the retro-areolar region of the left breast. The mean whole AGD was 29.2 mGy. The mean AGD due to CEM amounted to 73% of the whole AGD (21.2 mGy). The AGD attributable to the delayed phase of CEM contributed to 36% of the whole AGD (10.5 mGy). CONCLUSIONS: As we found no significant discrepancy between the readings of the two protocols, we conclude that delayed-phase image acquisition in CEM does not provide essential diagnostic benefits for effective disease management. Instead, it contributes to unnecessary radiation exposure.

Background parenchymal enhancement on contrast-enhanced mammography: associations with breast density and patient's characteristics.

PURPOSE: To evaluate if background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM), graded according to the 2022 CEM-dedicated Breast Imaging Reporting and Data System (BI-RADS) lexicon, is associated with breast density, menopausal status, and age. METHODS: This bicentric retrospective analysis included CEM examinations performed for the work-up of suspicious mammographic findings. Three readers independently and blindly evaluated BPE on recombined CEM images and breast density on low-energy CEM images. Inter-reader reliability was estimated using Fleiss κ. Multivariable binary logistic regression was performed, dichotomising breast density and BPE as low (a/b BI-RADS categories, minimal/mild BPE) and high (c/d BI-RADS categories, moderate/marked BPE). RESULTS: A total of 200 women (median age 56.8 years, interquartile range 50.5-65.6, 140/200 in menopause) were included. Breast density was classified as a in 27/200 patients (13.5%), as b in 110/200 (55.0%), as c in 52/200 (26.0%), and as d in 11/200 (5.5%), with moderate inter-reader reliability (κ = 0.536; 95% confidence interval [CI] 0.482-0.590). BPE was minimal in 95/200 patients (47.5%), mild in 64/200 (32.0%), moderate in 25/200 (12.5%), marked in 16/200 (8.0%), with substantial inter-reader reliability (κ = 0.634; 95% CI 0.581-0.686). At multivariable logistic regression, premenopausal status and breast density were significant positive predictors of high BPE, with adjusted odds ratios of 6.120 (95% CI 1.847-20.281, p = 0.003) and 2.416 (95% CI 1.095-5.332, p = 0.029) respectively. CONCLUSION: BPE on CEM is associated with well-established breast cancer risk factors, being higher in women with higher breast density and premenopausal status.

Quantitative assessment of full-width at half-maximum and detector energy threshold in X-ray imaging systems.

BACKGROUND: The response function of imaging systems is regularly considered to improve the qualified maps in various fields. More the accuracy of this function, the higher the quality of the images. METHODS: In this study, a distinct analytical relationship between full-width at half-maximum (FWHM) value and detector energy thresholds at distinct tube peak voltage of 100 kV has been addressed in X-ray imaging. The outcomes indicate that the behavior of the function is exponential. The relevant cut-off frequency and summation of point spread function S(PSF) were assessed at large and detailed energy ranges. RESULTS: A compromise must be made between cut-off frequency and FWHM to determine the optimal model. By detailed energy range, the minimum and maximum of S(PSF) values were revealed at 20 keV and 48 keV, respectively, by 2979 and 3073. Although the maximum value of FWHM occurred at the energy of 48 keV by 224 mm, its minimum value was revealed at 62 keV by 217 mm. Generally, FWHM value converged to 220 mm and S(PSF) to 3026 with small fluctuations. Consequently, there is no need to increase the voltage of the X-ray tube after the energy threshold of 20 keV. CONCLUSION: The proposed FWHM function may be used in designing the setup of the imaging parameters in order to reduce the absorbed dose and obtain the final accurate maps using the related mathematical suggestions.

A novel method to evaluate the transverse pedicle angles of the lower lumbar vertebrae using digital radiography.

To investigate a novel approach for establishing the transverse pedicle angle (TPA) of the lower lumbar spine using preoperative digital radiography (DR). Computed Tomography (CT) datasets of the lower lumbar were reconstructed using MIMICS 17.0 software and then imported into 3-matic software for surgical simulation and anatomical parameter measurement. A mathematical algorithm of TPA based on the Pythagorean theorem was established, and all obtained data were analyzed by SPSS software. The CT dataset from 66 samples was reconstructed as a digital model of the lower lumbar vertebrae (L3-L5), and the AP length/estimated lateral length for L3 between the right and left sides was statistically significant (P = 0.015, P = 0.005). The AP length of the right for L4 was smaller than that of the left after a paired t test was executed (P = 0.006). Both the width of the pedicle and the length of the pedicle (P2C1) were consistent with TPA (L3

Significant effect of image contrast enhancement on weld defect detection.

Weld defect inspection is an essential aspect of testing in industries field. From a human viewpoint, a manual inspection can make appropriate justification more difficult and lead to incorrect identification during weld defect detection. Weld defect inspection uses X-radiography testing, which is now mostly outdated. Recently, numerous researchers have utilized X-radiography digital images to inspect the defect. As a result, for error-free inspection, an autonomous weld detection and classification system are required. One of the most difficult issues in the field of image processing, particularly for enhancing image quality, is the issue of contrast variation and luminosity. Enhancement is carried out by adjusting the brightness of the dark or bright intensity to boost segmentation performance and image quality. To equalize contrast variation and luminosity, many different approaches have recently been put forth. In this research, a novel approach called Hybrid Statistical Enhancement (HSE), which is based on a direct strategy using statistical data, is proposed. The HSE method divided each pixel into three groups, the foreground, border, and problematic region, using the mean and standard deviation of a global and local neighborhood (luminosity and contrast). To illustrate the impact of the HSE method on the segmentation or detection stage, the datasets, specifically the weld defect image, were used. Bernsen and Otsu's methods are the two segmentation techniques utilized. The findings from the objective and visual elements demonstrated that the HSE approach might automatically improve segmentation output while effectively enhancing contrast variation and normalizing luminosity. In comparison to the Homomorphic Filter (HF) and Difference of Gaussian (DoG) approaches, the segmentation results for HSE images had the lowest result according to Misclassification Error (ME). After being applied to the HSE images during the segmentation stage, every quantitative result showed an increase. For example, accuracy increased from 64.171 to 84.964. In summary, the application of the HSE method has resulted in an effective and efficient outcome for background correction as well as improving the quality of images.

[Examination of Optimal Frequency Processing in X-ray Images for Occult Femoral Neck Fractures].

PURPOSE: Osteosclerotic images are known as an image appearance of occult femoral neck fractures in X-ray images. The aim of this study is to investigate frequency enhancement processing that improves the visibility of the osteosclerotic image. METHODS: We acquired three sclerotic bone images with different thicknesses, and self-made bone equivalent phantoms were set up on a pelvic phantom. The frequency processing type and high-density enhancement coefficients were applied to the X-ray images taken at RF-A(1.0, 2.0), C(2.0, 4.0), D(1.0), and H(2.0, 4.0). For the physical index, we compared the difference in signal values between the sclerotic and background normal bone. We evaluated the preference using Scheffé's paired comparison methods for the visual index. RESULTS: For the physical index, RF-C(4.0) had the most significant signal value difference for all 3 bone stiffness images. For the visual index, RF-C(4.0) showed the highest preference. CONCLUSION: Using frequency-enhanced processing, RF-C(4.0) was suggested to improve the visibility of the osteosclerosis image.

Health technology assessment in musculoskeletal radiology: the case study of EOSedge™.

OBJECTIVES: Health technology assessment (HTA) is a systematic process used to evaluate the properties and effects of healthcare technologies within their intended use context. This paper describes the adoption of HTA process to assess the adoption of the EOSedge™ system in clinical practice. METHODS: The EOSedge™ system is a digital radiography system that delivers whole-body, high-quality 2D/3D biplanar images covering the complete set of musculoskeletal and orthopedic exams. Full HTA model was chosen using the EUnetHTA Core Model® version 3.0. The HTA Core Model organizes the information into nine domains. Information was researched and obtained by consulting the manufacturers' user manuals, scientific literature, and institutional sites for regulatory aspects. RESULTS: All nine domains of the EUnetHTA Core Model® helped conduct the HTA of the EOSedge, including (1) description and technical characteristics of the technology; (2) health problem and current clinical practice; (3) safety; (4) clinical effectiveness; (5) organizational aspects; (6) economic evaluation; (7) impact on the patient; (8) ethical aspects; and (9) legal aspects. CONCLUSIONS: EOS technologies may be a viable alternative to conventional radiographs. EOSedge has the same intended use and similar indications for use, technological characteristics, and operation principles as the EOS System and provides significant dose reduction factors for whole spine imaging compared to the EOS System without compromising image quality. Regarding the impact of EOS imaging on patient outcomes, most studies aim to establish technical ability without evaluating their ability to improve patient outcomes; thus, more studies on this aspect are warranted.

Digital Breast Tomosynthesis for Upgraded BIRADS Scoring towards the True Pathology of Lesions Detected by Contrast-Enhanced Mammography.

OBJECTIVE: To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM). MATERIAL AND METHODS: A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study. RESULTS: BIRADS scores of CEM-detected lesions were upgraded toward the lesion's pathology with the addition of DBT (p > 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins. CONCLUSIONS: The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score.

Image fusion-based low-dose CBCT enhancement method for visualizing miniscrew insertion in the infrazygomatic crest.

Digital dental technology covers oral cone-beam computed tomography (CBCT) image processing and low-dose CBCT dental applications. A low-dose CBCT image enhancement method based on image fusion is proposed to address the need for subzygomatic small screw insertion. Specifically, firstly, a sharpening correction module is proposed, where the CBCT image is sharpened to compensate for the loss of details in the underexposed/over-exposed region. Secondly, a visibility restoration module based on type II fuzzy sets is designed, and a contrast enhancement module using curve transformation is designed. In addition to this, we propose a perceptual fusion module that fuses visibility and contrast of oral CBCT images. As a result, the problems of overexposure/underexposure, low visibility, and low contrast that occur in oral CBCT images can be effectively addressed with consistent interpretability. The proposed algorithm was analyzed in comparison experiments with a variety of algorithms, as well as ablation experiments. After analysis, compared with advanced enhancement algorithms, this algorithm achieved excellent results in low-dose CBCT enhancement and effective observation of subzygomatic small screw implantation. Compared with the best performing method, the evaluation metric is 0.07-2 higher on both datasets. The project can be found at: https://github.com/sunpeipei2024/low-dose-CBCT .

PSF and MTF from a bar pattern in digital mammography.

Background.The MTF has difficulties being determined (according to the provisions of the IEC standards) in the hospital setting due to the lack of resources.Purpose.The objective of this work is to propose a quantitative method for obtaining the point spread function (PSF) and the modulation transfer function (MTF) of a digital mammography system from an image of a bar pattern.Methods.The method is based on the measurement of the contrast transfer function (CTF) of the system over the image of the bar pattern. In addition, a theoretical model for thePSFis proposed, from which the theoreticalCTFof the system is obtained by means of convolution with a square wave (mathematical simulation of the bar pattern). Through an iterative process, the free parameters of thePSFmodel are varied until the experimentalCTFcoincides with the one calculated by convolution. Once thePSFof the system is obtained, we calculate theMTFby means of its Fourier transform. TheMTFcalculated from the modelPSFhave been compared with those calculated from an image of a 65µm diameter gold wire using an oversampling process.Results.TheCTFhas been calculated for three digital mammographic systems (DMS 1, DMS 2 and DMS 3), no differences of more than 5 % were found with the CTF obtained with the PSF model. The comparison of theMTFshows us the goodness of thePSFmodel.Conclusions.The proposed method for obtainingPSFandMTFis a simple and accessible method, which does not require a complex configuration or the use of phantoms that are difficult to access in the hospital world. In addition, it can be used to calculate other magnitudes of interest such as the normalized noise power spectrum (NNPS) and the detection quantum efficiency (DQE).